Bioorthogonal "Click and Release" Reaction-Triggered Aggregation of Gold Nanoparticles Combined with Released Lonidamine for Enhanced Cancer Photothermal Therapy.

Cancer has been the most deadly disease, and 13 million cancer casualties are estimated to occur each year by 2030. Gold nanoparticles (AuNPs)-based photothermal therapy (PTT) has attracted great interest due to its high spatiotemporal controllability and noninvasiveness. Due to the trade-off between particle size and photothermal efficiency of AuNPs, rational design is needed to realize aggregation of AuNPs into larger particles with desirable NIR adsorption in tumor site. Exploiting the bioorthogonal "Click and Release" (BCR) reaction between iminosydnone and cycloalkyne, aggregation of AuNPs can be achieved and attractively accompanied by the release of chemotherapeutic drug purposed to photothermal synergizing. We synthesize iminosydnone-lonidamine (ImLND) as a prodrug and choose dibenzocyclooctyne (DBCO) as the trigger of BCR reaction. A PEGylated AuNPs-based two-component nanoplatform consisting of prodrug-loaded AuNPs-ImLND and tumor-targeting peptide RGD-conjugated AuNPs-DBCO-RGD is designed. In the therapeutic regimen, AuNPs-DBCO-RGD are intravenously injected first for tumor-specific enrichment and retention. Once the arrival of AuNPs-ImLND injected later at tumor site, highly photothermally active nanoaggregates of AuNPs are formed via the BCR reaction between ImLND and DBCO. The simultaneous release of lonidamine further enhanced the therapeutic performance by sensitizing cancer cells to PTT.

Hybrid Vesicles Based on Autologous Tumor Cell Membrane and Bacterial Outer Membrane To Enhance Innate Immune Response and Personalized Tumor Immunotherapy.

Tumor heterogeneity, often leading to metastasis, limits the development of tumor therapy. Personalized therapy is promising to address tumor heterogeneity. Here, a vesicle system was designed to enhance innate immune response and amplify personalized immunotherapy. Briefly, the bacterial outer membrane vesicle (OMV) was hybridized with the cell membrane originated from the tumor (mT) to form new functional vesicles (mTOMV). In vitro experiments revealed that the mTOMV strengthened the activation of innate immune cells and increased the specific lysis ability of T cells in homogeneous tumors. In vivo experiments showed that the mTOMV effectively accumulated in inguinal lymph nodes, then inhibited lung metastasis. Besides, the mTOMV evoked adaptive immune response in homologous tumor rather than the heterogeneous tumor, reversibly demonstrating the effects of personalized immunotherapy. The functions to inhibit tumor growth and metastasis accompanying good biocompatibility and simple preparation procedure of mTOMV provide their great potential for clinical applications.

Identification of discriminating chemical compounds in banana species and their odor characterization using GC-MS, statistical, and clustering analysis.

The study aims identification of discriminating chemical constituents in the banana odor grown in Philippines and Ecuador using GC-MS characterization. Ester is recognized as a major chemical class in selected banana odor. Odors discriminating compounds like, 2-hexenal, ethyl acetate, and hexanoic acid, ethyl ester, etc. have been identified. Besides, other odors generating chemical compounds (alcohols, esters, aldehydes, and ketones) have been recognized. Furthermore, principal component analysis (PCA) and hierarchical cluster analysis were implemented to differentiate banana odors. PCA achieved 100% discrimination of selected bananas odors using the peak area information about recognizing chemical compounds. Odor identity and discrimination of selected bananas have been achieved successfully. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13197-021-05298-9.

2,4,6-Trinitrophenol detection by a new portable sensing gadget using carbon dots as a fluorescent probe.

An optical sensing gadget using fluorescence of carbon dots (CDs) was developed to realize the in-field detection of 2,4,6-trinitrophenol (TNP) in tap water and lake water samples. Fluorescent CDs were prepared through a one-step hydrothermal synthetic route. The fluorescence spectra demonstrated that the CDs could specifically discriminate TNP from other nitroaromatic explosives in an aqueous medium. The fluorescence of the CDs was quenched linearly with the concentration of TNP in the range from 1 to 100 µM, with a detection limit of 0.48 µM (3σ/k). The detection mechanism was ascribed to the synergistic effect of the inner filter effect and electron transfer. In addition, a portable sensing gadget based on a high-precision RGB color sensor and a micro control unit was developed. With use of the sensing gadget and the CDs, TNP detection in tap water and lake water samples was realized. Importantly, the portable sensing gadget combined with highly stable, low-toxicity, and sensitive CDs might have great potential for application in extensive in-field sensing situations. Graphical abstract Carbon dots synthesized with 4-(diethylamino)salicylaldehyde as the initial material were used for 2,4,6-trinitrophenol (TNP) detection. TNP quenches the fluorescence of carbon dots, and the mechanism is ascribed to the synergistic effect of the inner filter effect and electron transfer. A portable sensing gadget based on a 32-bit micro control unit was successfully applied for in-field TNP detection.

Diblock Polymer Brush (PHEAA- b-PFMA): Microphase Separation Behavior and Anti-Protein Adsorption Performance.

In this paper, a series of amphiphilic diblock polymers of poly(hydroxyethylacrylamide)- b-poly(1H,1H-pentafluoropropyl methacrylate) (PHEAA- b-PFMA) were grafted from silicon wafer via surface-initiated atom transfer radical polymerization (SI-ATRP). Surface wettability and chemical compositions of the modified surfaces were characterized by contact angle goniometer and X-ray photoelectron spectroscopy (XPS) respectively. Molecular weight and polydispersity of each block were measured using gel permeation chromatography (GPC). The topography and the microphase separation behavior of PHEAA- b-PFMA surfaces were investigated by atomic force microscope (AFM). The results show that only when the grafting density (σ) and thickness of PHEAA brush were in the range of 0.9-1.3 (chain/nm2) and 6.6-15.1 nm, respectively, and the ratio of PFMA/PHEAA varied from 89/42 to 89/94, could the diblock copolymer phase separate into nanostructures. Further, the antiprotein adsorption performance of the modified surfaces against BSA, fibrinogen, and lysozyme was studied. The results indicated the modified surfaces could reduce the protein adsorption compared to the pristine silicon wafer. For Fibrinogen, the antiadsorption effect of PHEAA- b-PFMA-modified surfaces with microphase segregation was better than that of corresponding PHEAA modified surfaces. The results provide further evidence that surface composition and microphase segregation of fluorinated moieties of block copolymer brushes significantly impact protein adsorption behaviors.

Machine-Learning-Based Olfactometer: Prediction of Odor Perception from Physicochemical Features of Odorant Molecules.

Gas chromatography/olfactometry (GC/O) has been used in various fields as a valuable method to identify odor-active components from a complex mixture. Since human assessors are employed as detectors to obtain the olfactory perception of separated odorants, the GC/O technique is limited by its subjectivity, variability, and high cost of the trained panelists. Here, we present a proof-of-concept model by which odor information can be obtained by machine-learning-based prediction from molecular parameters (MPs) of odorant molecules. The odor prediction models were established using a database of flavors and fragrances including 1026 odorants and corresponding verbal odor descriptors (ODs). Physicochemical parameters of the odorant molecules were acquired by use of molecular calculation software (DRAGON). Ten representative ODs were selected to build the prediction models based on their high frequency of occurrence in the database. The features of the MPs were extracted via either unsupervised (principal component analysis) or supervised (Boruta, BR) approaches and then used as input to calibrate machine-learning models. Predictions were performed by various machine-learning approaches such as support vector machine (SVM), random forest, and extreme learning machine. All models were optimized via parameter tuning and their prediction accuracies were compared. A SVM model combined with feature extraction by BR-C (confirmed only) was found to afford the best results with an accuracy of 97.08%. Validation of the models was verified by using the GC/O data of an apple sample for comparison between the predicted and measured results. The prediction models can be used as an auxiliary tool in the existing GC/O by suggesting possible OD candidates to the panelists and thus helping to give more objective and correct judgment. In addition, a machine-based GC/O in which the panelist is no longer needed might be expected after further development of the proposed odor prediction technique.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes.

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

A host plant genome (Zizania latifolia) after a century-long endophyte infection.

Despite the importance of host-microbe interactions in natural ecosystems, agriculture and medicine, the impact of long-term (especially decades or longer) microbial colonization on the dynamics of host genomes is not well understood. The vegetable crop 'Jiaobai' with enlarged edible stems was domesticated from wild Zizania latifolia (Oryzeae) approximately 2000 years ago as a result of persistent infection by a fungal endophyte, Ustilago esculenta. Asexual propagation via infected rhizomes is the only means of Jiaobai production, and the Z. latifolia-endophyte complex has been maintained continuously for two centuries. Here, genomic analysis revealed that cultivated Z. latifolia has a significantly smaller repertoire of immune receptors compared with wild Z. latifolia. There are widespread gene losses/mutations and expression changes in the plant-pathogen interaction pathway in Jiaobai. These results show that continuous long-standing endophyte association can have a major effect on the evolution of the structural and transcriptomic components of the host genome.

Water-soluble photoluminescent fullerene capped mesoporous silica for pH-responsive drug delivery and bioimaging.

In this paper, a biocompatible and water-soluble fluorescent fullerene (C60-TEG-COOH) coated mesoporous silica nanoparticle (MSN) was successfully fabricated for pH-sensitive drug release and fluorescent cell imaging. The MSN was first reacted with 3-aminopropyltriethoxysilane to obtain an amino-modified MSN, and then the water-soluble C60 with a carboxyl group was used to cover the surface of the MSN through electrostatic interaction with the amino group in PBS solution (pH = 7.4). The release of doxorubicin hydrochloride (DOX) could be triggered under a mild acidic environment (lysosome, pH = 5.0) due to the protonation of C60-TEG-COO-, which induced the dissociation of the C60-TEG-COOH modified MSN (MSN@C60). Furthermore, the uptake of nanoparticles by cells could be tracked because of the green fluorescent property of the C60-modified MSN. In an in vitro study, the prepared materials showed excellent biocompatibility and the DOX-loaded nanocarrier exhibited efficient anticancer ability. This work offered a simple method for designing a simultaneous pH-responsive drug delivery and bioimaging system.

Molecularly Imprinted Filtering Adsorbents for Odor Sensing.

Versatile odor sensors that can discriminate among huge numbers of environmental odorants are desired in many fields, including robotics, environmental monitoring, and food production. However, odor sensors comparable to an animal's nose have not yet been developed. An animal's olfactory system recognizes odor clusters with specific molecular properties and uses this combinatorial information in odor discrimination. This suggests that measurement and clustering of odor molecular properties (e.g., polarity, size) using an artificial sensor is a promising approach to odor sensing. Here, adsorbents composed of composite materials with molecular recognition properties were developed for odor sensing. The selectivity of the sensor depends on the adsorbent materials, so specific polymeric materials with particular solubility parameters were chosen to adsorb odorants with various properties. The adsorption properties of the adsorbents could be modified by mixing adsorbent materials. Moreover, a novel molecularly imprinted filtering adsorbent (MIFA), composed of an adsorbent substrate covered with a molecularly imprinted polymer (MIP) layer, was developed to improve the odor molecular recognition ability. The combination of the adsorbent and MIP layer provided a higher specificity toward target molecules. The MIFA thus provides a useful technique for the design and control of adsorbents with adsorption properties specific to particular odor molecules.

Transcriptional Changes in nAChRs, Interactive Proteins and P450s in Locusta migratoria manilensis (Orthoptera: Acrididae) CNS in Response to High and Low Oral Doses of Imidacloprid.

The insect central nervous system (CNS) is the target for many insecticides, and changes in transcript levels could be expected after insecticide applications. In this study, differentially expressed genes in the locust (Locusta migratoria manilensis) CNS in response to imidacloprid treatments at low dose (LD, 10% mortality) and high dose (HD, 80% mortality) were identified. Two nicotine acetylcholine receptor (nAChR) subunits genes and 18 interacting protein genes were regulated at LD, and only one nAChR subunit gene and 11 interacting proteins were regulated at HD. Among the 110 annotated P450 unigenes, 43 unigenes were regulated at LD and 34 unigenes were regulated at HD. Most of the differentially expressed P450 unigenes were mapped to CYP4, in which most unigenes were upregulated at LD, but downregulated at HD. Totally, the numbers and regulation levels of the regulated genes were more at LD than that at HD. Seventeen unigenes were selected to test their expression changes following insecticide treatments by qRT-PCR, in which the changes in more than half of the selected genes were verified. The results revealed the variation in the response of locusts to different insecticide pressure, such as different doses.

[Research on Improving the Measurement Speed of THz-TDS Instruments].

The measurement speed is an important parameter of terahertz time-domain spectroscopy (THz-TDS) instruments. To improve the measurement speed of the spectrometer we need to increase the scanning speed of the delay line. In this paper, we study the influence of the scanning speed, the time constant of lock-in amplifier and the sampling rate on the signal quality. The results show that, when the time constant equal to 10 ms, increasing the scanning speed does not cause significant changes in the amplitude of the signal. But when the time constant equal to 30, 100 and 300 ms, with the increasing of the scanning speed the signal amplitude decreases rapidly. Therefore, the time constant should be set as small as possible to avoid deterioration of signal quality. On the other hand, higher the scanning speed is, fewer data points are collected with a same time-domain length. Therefore, when the scanning speed increase, not only the time constant should be reduced, but also the sampling rate should be increased to avoid the distortion of signal waveform caused by the number reduction of data points. The conclusions can provide a reference for improving the measurement speed of THz-TDS instrument.

A PD-L1-targeting Regulator for Metabolic Reprogramming to Enhance Glutamine Inhibition-Mediated Synergistic Antitumor Metabolic and Immune Therapy.

Inhibition of glutamine metabolism in tumor cells can cause metabolic compensation-mediated glycolysis enhancement and PD-L1 upregulation-induced immune evasion, significantly limiting the therapeutic efficacy of glutamine inhibitors. Here, inspired by the specific binding of receptor and ligand, a PD-L1-targeting metabolism and immune regulator (PMIR) are constructed by decorating the glutaminase inhibitor (BPTES)-loading zeolitic imidazolate framework (ZIF) with PD-L1-targeting peptides for regulating the metabolism within the tumor microenvironment (TME) to improve immunotherapy. At tumor sites, PMIR inhibits glutamine metabolism of tumor cells for elevating glutamine levels within the TME to improve the function of immune cells. Ingeniously, the accompanying PD-L1 upregulation on tumor cells causes self-amplifying accumulation of PMIR through PD-L1 targeting, while also blocking PD-L1, which has the effects of converting enemies into friends. Meanwhile, PMIR exactly offsets the compensatory glycolysis, while disrupting the redox homeostasis in tumor cells via the cooperation of components of the ZIF and BPTES. These together cause immunogenic cell death of tumor cells and relieve PD-L1-mediated immune evasion, further reshaping the immunosuppressive TME and evoking robust immune responses to effectively suppress bilateral tumor progression and metastasis. This work proposes a rational strategy to surmount the obstacles in glutamine inhibition for boosting existing clinical treatments.

The Effect of Everyday Moral Sensitivity on Bullying Bystander Behavior: Parallel Mediating Roles of Empathy and Moral Disengagement.

The higher moral sensitivity to bullying a student has, the more likely they are to help the victim or inhibit bullying rather than ignore it. Research has mainly focused on particular sensitivity to bullying, and it remains unknown whether sensitivity to everyday moral issues functions similarly. The present study aimed to examine the effect of everyday moral sensitivity (EMS) on bullying bystander behaviors. We included a range of school children (n = 1,655, Grades 3-12, 27.6% girls) in Southwest China. The results show 6.10% have been a victim-only, 0.48% have been a bully-only, 0.85% have been the bullying victim, 92.57% have been neither a bully nor a bullying victim, and 45.86% have observed bullying. Students in lower grades are more likely to be bullied. After controlling for covariates (i.e., gender, grade, and social desirability), EMS is positively associated with positive bystander behaviors. Moreover, empathy and moral disengagement (MD) play a mediating role in the relationship between EMS and positive bystander behaviors. The results reveal two parallel processes of EMS influenced bystander behaviors (i.e., empathy and MD). The findings indicate the possibility of cultivating EMS and highlight the role of morality development in preventing school bullying.

A Domain Generative Graph Network for EEG-Based Emotion Recognition.

Emotion is a human attitude experience and corresponding behavioral response to objective things. Effective emotion recognition is important for the intelligence and humanization of brain-computer interface (BCI). Although deep learning has been widely used in emotion recognition in recent years, emotion recognition based on electroencephalography (EEG) is still a challenging task in practical applications. Herein, we proposed a novel hybrid model that employs generative adversarial networks to generate potential representations of EEG signals while combining graph convolutional neural networks and long short-term memory networks to recognize emotions from EEG signals. Experimental results on DEAP and SEED datasets show that the proposed model achieved the promising emotion classification performance compared with the state-of-the-art methods.

New Wine in an Old Bottle? Exposure to Bullying-Related Media and Bullying Perpetration Behavior in Daily Life Among Adolescents.

Although the effect of media violence on aggression has garnered major attention, little is known about the link between bullying-related media exposure and bullying behaviors. Across three studies, we examined this association among Chinese adolescents. Study 1 used a large sample of adolescents (n=10,391, 51.4% boys) to investigate the link between bullying-related media exposure and bullying perpetration. Using another adolescent sample (n=3,125, 49.5% boys), Study 2 replicated the findings from Study 1 and extended the investigation from traditional bullying to cyberbullying perpetration. Study 3 examined the longitudinal associations between bullying-related media exposure and (cyber)bullying perpetration 6 months later (n = 2,744, 47.0% boys). The results suggested a positive, albeit small, association between exposure to bullying-related media and (cyber)bullying perpetration. Importantly, personal anti-bullying attitudes moderated this link, with a significant association observed among adolescents holding weak anti-bullying attitudes. Findings are discussed with respect to the media's effect on bullying behaviors.

Engineering metal-based hydrogel-mediated tertiary lymphoid structure formation via activation of the STING pathway for enhanced immunotherapy.

Tertiary lymphoid structures (TLSs) primarily constructed by multiple immune cells can effectively enhance tumor immune responses, but expediting the formation of TLSs is still an enormous challenge. Herein, a stimulator of interferon gene (STING)-activating hydrogel (ZCCG) was elaborately developed by coordinating Zn2+ with 4,5-imidazole dicarboxylic acid, and simultaneously integrating chitosan (a stimulant of STING pathway activation) and CpG (an agonist of toll-like receptor 9, TLR9) for initiating and activating cGAS-STING and TLR9 pathway-mediated immunotherapy. Moreover, the dual-pathway activation could effectively enhance the infiltration of immune cells and the expression of lymphocyte-recruiting chemokines in the tumor microenvironment (TME), thereby promoting the formation of TLSs and further strengthening tumoricidal immunity. Local administration of the hydrogel could prime systemic immune responses and long-term immune memory and improve the therapeutic effects of programmed death-1 antibody (αPD-1) to inhibit tumor progression, metastasis and recurrence. The engineered hydrogel lays the foundation for tumor immunotherapy strategies based on the enhanced formation of TLSs via the activation of the cGAS-STING and TLR9 pathways.

Alginate/CaCO3 hybrid nanoparticles for efficient codelivery of antitumor gene and drug.

In this study, a facile strategy for efficient codelivery of gene and drug was developed. Using a coprecipitation method, doxorubicin hydrochloride (DOX), an antitumor drug, and p53 expression plasmid were encapsulated in alginate/CaCO(3)/DNA/DOX nanoparticles with high encapsulation efficiency. The in vitro cell inhibition effect of the alginate/CaCO(3)/DNA/DOX nanoparticles was evaluated by MTT assay in HeLa cells. The alginate/CaCO(3)/DNA/DOX nanoparticles exhibited a high cell inhibition rate about 80%, indicating that the alginate/CaCO(3)/DNA/DOX nanoparticles could effectively mediate gene transfection and deliver the drug to the cells. Compared with the codelivery of gene and drug, the treatments by alginate/CaCO(3)/DOX nanoparticles and alginate/CaCO(3)/DNA nanoparticles separately led to much lower cell inhibition rates. Compared with the CaCO(3)/DNA/DOX nanoparticles without alginate modification, the alginate/CaCO(3)/DNA/DOX nanoparticles with a decreased particle size exhibited enhanced delivery efficiency. The alginate/CaCO(3)/DNA/DOX nanoparticles have promising applications in cancer treatments.

Resolving the Limitations of the CNI Model in Moral Decision Making Using the CAN Algorithm: A Methodological Contrast.

The CNI model generates C, N, and I parameters to measure people's mental processes-consequence sensitivity (C), norm sensitivity (N), and generalized inaction/action preferences (I)-in moral decision making. Given the limitations of the CNI model, the CAN algorithm was developed to depict the consequence sensitivity (C), overall action versus inaction preferences (A), norm sensitivity (N), and perverse responses with the other three parameters. However, no studies have clarified whether and how the CAN algorithm can solve the limitations of the CNI model. The present study systematically uncovers the limitations of the CNI model and the solutions provided by the CAN algorithm: (a) the CNI model does not consider negative values of the parameters, but the CAN algorithm does; (b) the sequential processing assumption of the CNI model is biased, the CAN algorithm proposes a parallel calculation strategy to fix this problem; (c) the calculation of the I parameter of the CNI model is inaccurate, so the CAN algorithm proposes the A parameter to replace it; (d) the CNI model has a problem measuring perverse responses, while the CAN algorithm develops three parameters to measure these. We examined some of our points on the basis of a reanalysis of the foreign language effect (FLE) by comparing the parameters from the CAN algorithm with those from the CNI model. We found that consequence and norm sensitivity were estimated to be greater using the CNI model than with the CAN algorithm. Consequently, these overestimations significantly (consequence sensitivity) and marginally (norm sensitivity) interfered with the FLE, making the FLE more likely to return a false positive result. In addition, the CAN algorithm was able to measure the extent of perverse responses, indicating that foreign language (compared to a native language) leads to more perverse responses. The present study demonstrates that the CNI model magnifies the Type I error of conclusions and that the CAN algorithm (compared to the CNI model) provides more insights regarding moral decision making.

People Cheat on Task Performance When They Feel Bored: The Mediating Role of State Self-Efficacy.

It is unclear whether the state of boredom is related to morality. The present study investigated how state boredom influenced cheating behaviors on task performance. In Study 1 (N = 104), participants were induced to feel bored, and then reported whether they had finished an anagram task (two sentences in the task were unsolvable). The results found that people with higher boredom showed more cheating behaviors than those with lower boredom on task performance. In Study 2 (N = 139), participants completed the Multidimensional State Boredom Scale, and then completed the same anagram task as in Study 1, as well as a state self-efficacy scale. The results revealed that state self-efficacy mediated the effect of state boredom on cheating behaviors on task performance. In other words, a higher level of state boredom leads to a lower level of state self-efficacy, and the lower state self-efficacy then results in more cheating behaviors. The present study provides empirical evidence that state boredom has its moral function through state self-efficacy.